Instructions to use devkya/custom-whiper-small-you-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
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How to use devkya/custom-whiper-small-you-v1 with PEFT:
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custom-whiper-small-you-v1
This model is a fine-tuned version of SungBeom/whisper-small-ko on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 2.0737
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.3391 | 125.0 | 500 | 2.1300 |
| 4.9716 | 250.0 | 1000 | 2.0881 |
| 4.8699 | 375.0 | 1500 | 2.0737 |
Framework versions
- PEFT 0.10.0
- Transformers 4.41.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for devkya/custom-whiper-small-you-v1
Base model
SungBeom/whisper-small-ko